Robotic devices are used in many processes for transport of articles in predetermined paths. For instance, robots are used in semiconductor manufacturing to perform tasks such as selecting semiconductor wafers from carrier cassettes, placing them in process chambers, moving them between process chambers, and placing them back into cassettes for transport to a subsequent operation. These robots must operate at very high speeds to assure that tool throughput is not limited by wafer transport, but must also place wafers at their desired location within fractions of a millimeter in three-dimensional space. Because of these requirements, robots used in semiconductor manufacturing are taught the locations for picking up, transporting, and depositing wafers, and are expected to consistently maneuver precisely among those locations repeatedly for months at a time.
If wafers are misplaced by even a small amount, several handling errors are possible. These errors may become evident by some type of physical interference during wafer transport. The wafer may scrape or hit a tool or cassette surface, resulting in either broken wafers or scratched wafer surfaces that ruin any chips at the scratched location. In addition, the robot may cause impact collisions between the wafer and tool surfaces that are too slight to break wafers, but are sufficient to nick the wafer edge. These nicked wafers are then highly likely to break during high-stress process steps such as the polish or heat treatment steps. Finally, the robot itself may be the source of physical interference via rubbing at a joint or on a tool surface, resulting in elevated levels of foreign material particulate matter that may lead to decreased wafer yield and lower productivity.
No real-time method is available to determine if misaligned wafer placement is causing scratches or collisions, or to determine if the robot is rubbing against a surface and causing particulate generation. Periodic foreign material checks will not catch an intermittent problem or find a problem that is just beginning. Because often the same type of robot is used on multiple types of process tools, it is difficult to determine which robot is responsible once a problem has been identified. This difficulty is exacerbated if the problem is intermittent.
Several systems are known for sensing or preventing robot handling errors, including the use of force sensors, strain gauges, or limit switches on the robot arm. Such systems are capable of detecting large or forceful collisions. They cannot detect, however, the very slight physical interference produced by gently scratching or nicking the wafer on a tool surface, or by rubbing at the robot joints.
It is also known to mount active acoustic or light-radiation devices on robots to actively generate a "visual" map of the robot environment, from which the robot makes navigation decisions and avoids collisions. Such systems require a great deal of resources dedicated to active monitoring and mapping. They still may not detect slight physical interference, however, such as rubbing of parts of the robot not within the field of "vision."
The use of magnetic fields created by placing magnetic strips in the robot arm and in the tool area, and using a field sensor to detect abnormalities in a previously characterized field pattern, has also been used to sense collisions. Such a pattern may not detect slight physical interference between wafers and work surfaces, however, because the relationship between the robot and the tool may be essentially the same for a non-interfering motion and a slight interfering motion. Also, the specific set-up required for mapping every robot motion and every robot geometry is time-consuming and expensive.
In view of the shortcomings of the known systems, there remains a need for an improved structure and method for detection of robot handling errors.